将值分配给R中另一个环境中的对象的一部分

Question

假设我在环境e中定义了两个类似的大对象x，y（datatable）。 我想用类似的方法改变x或y的很大一部分，而不用在f的执行环境中创建x或y的副本。例如：

e <- new.env() 
e$x <- c(1,2,3) # imagine this to be BIG (ie. dataframe with 200k vars each 500k rows) 
e$y <- c(4,5,6) # same here 
e$v <- 2  # minor variables 

f <- function(var_str, env, input){ 

    # do some computation on parts of var_str which is either "x" or "y" 
    # and store these right back into e$x or e$y, respectively. 
    # ie 

    str <- paste0(var_str,"[2:3] <- (",var_str,"[2:3])^2 + rep(v,2) + ", deparse(input1),"^3/c(100,101)") 
    eval(parse(text=str), envir= e) 

    # this does work but I can image there is an easier/more elegant way 
    # of doing this. 
} 

我想定义在全球环境的功能，该功能适用​​于E $ x和E $ y随输入不同的变量。 IE浏览器。执行

f("x", e, c(1,2)) 
f("y", e, c(3,4)) 

有没有人有一个优雅的解决方案。

Answer 1

出于好奇，我试着用the simple example in the R6 tutorial工作以及与此想出了（复制作为控制台成绩单）。我真的不知道它是否符合请求的非复制要求，但它似乎是在原地修改对象。

# Assumes one has created an R6 constructor named `RC` ... 
# slightly extended from the example in section 
RC <- setRefClass("RC", 
    fields = list(x = 'ANY'), 
    methods = list(
    getx = function() x, 
    setx = function(value) x <<- value, 
    setsub = function(i,j,val) x[i,j] <<- val 
) 
) 

#--- execution --- 
rc <- RC$new() 
rc$setx(matrix(1:20, 4,5)) 
rc 
# --- result ---  
Reference class object of class "RC" 

Field "x": 
    [,1] [,2] [,3] [,4] [,5] 
[1,] 1 5 9 13 17 
[2,] 2 6 10 14 18 
[3,] 3 7 11 15 19 
[4,] 4 8 12 16 20 

测试类特定的setsub功能：

rc$setsub(4,5,0) #Test of setting a single element within an object to a new value 
rc 
#-------  
Reference class object of class "RC" 
Field "x": 
    [,1] [,2] [,3] [,4] [,5] 
[1,] 1 5 9 13 17 
[2,] 2 6 10 14 18 
[3,] 3 7 11 15 19 
[4,] 4 8 12 16 0 

rc$setsub(1:4,1:4,0) #Test of setting a range of elements within an object to a new value 
rc 
# --------- 
Reference class object of class "RC" 
Field "x": 
    [,1] [,2] [,3] [,4] [,5] 
[1,] 0 0 0 0 17 
[2,] 0 0 0 0 18 
[3,] 0 0 0 0 19 
[4,] 0 0 0 0 0 

所以通过setsub这个（看得很轻测试）实施[<- -function的确实成功。使用self参考一个单一的努力来扩展这个例子确实失败了。

Answer 2

eval(parse())是要避免的。您可以参考的环境是这样的：

e <- new.env() 
e$x <- c(1,2,3) # imagine this to be BIG (ie. dataframe with 200k vars each 500k rows) 
e$y <- c(4,5,6) # same here 
e$v <- 2  # minor variables 

f <- function(var_str, env, input){ 

    # do some computation on parts of var_str which is either "x" or "y" 
    # and store these right back into e$x or e$y, respectively. 
    # ie 
    env[[var_str]][2:3] <- (env[[var_str]][2:3])^2 + rep(env$v,2) + input^3/input 

} 


f("x", e, 1:2) 
e$x 
#[1] 1 7 15